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J Am Med Inform Assoc 2008;15:513-523 doi:10.1197/jamia.M2501
  • The Practice of Informatics
  • Application of Information Technology

“Smart Forms” in an Electronic Medical Record: Documentation-based Clinical Decision Support to Improve Disease Management

  1. Jeffrey L Schnippera,d,
  2. Jeffrey A Lindera,d,
  3. Matvey B Palchukb,c,
  4. Jonathan S Einbindera,b,c,d,
  5. Qi Lib,c,
  6. Anatoly Postilnikb,
  7. Blackford Middletona,b,c,d
  1. aDivision of General Medicine, Brigham and Women's Hospital, Boston, MA
  2. bPartners Healthcare Information Systems, Boston, MA
  3. cClinical Informatics Research & Development, Partners HealthCare System, Boston, MA
  4. dHarvard Medical School, Boston, MA
  1. Correspondence: Jeffrey L. Schnipper, MD, MPH, Division of General Medicine, Brigham and Women's Hospital, 1620 Tremont Street, Boston, MA 02120-1613 (Email: <jschnipper{at}partners.org>)
  • Received 8 May 2007
  • Accepted 7 February 2008

Abstract

Clinical decision support systems (CDSS) integrated within Electronic Medical Records (EMR) hold the promise of improving healthcare quality. To date the effectiveness of CDSS has been less than expected, especially concerning the ambulatory management of chronic diseases. This is due, in part, to the fact that clinicians do not use CDSS fully. Barriers to clinicians' use of CDSS have included lack of integration into workflow, software usability issues, and relevance of the content to the patient at hand. At Partners HealthCare, we are developing “Smart Forms” to facilitate documentation-based clinical decision support. Rather than being interruptive in nature, the Smart Form enables writing a multi-problem visit note while capturing coded information and providing sophisticated decision support in the form of tailored recommendations for care. The current version of the Smart Form is designed around two chronic diseases: coronary artery disease and diabetes mellitus. The Smart Form has potential to improve the care of patients with both acute and chronic conditions.

Footnotes

  • This study was supported by a grant from the Agency for Healthcare Research and Quality (1 R01 HS015169-01). Dr. Schnipper is supported by a mentored career development award from the National Heart Lung and Blood Institute (1 K08 HL072806-01). Dr. Linder is supported by a career development award (K08 HS014563) from the Agency for Healthcare Research and Quality.

  • Portions of this paper were presented at the 2006 Annual Symposium of the American Medical Informatics Association, Washington, DC.

  • There are no commercial or financial relationships that could pose a conflict of interest with the material presented in this paper.

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